Overview

Dataset statistics

Number of variables28
Number of observations89
Missing cells19
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory225.4 B

Variable types

Numeric9
Categorical19

Alerts

airdate has constant value "2020-12-28" Constant
_embedded_show_dvdCountry has constant value "nan" Constant
url has a high cardinality: 89 distinct values High cardinality
name has a high cardinality: 71 distinct values High cardinality
_embedded_show_url has a high cardinality: 54 distinct values High cardinality
_embedded_show_name has a high cardinality: 54 distinct values High cardinality
_links_self_href has a high cardinality: 89 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_weight is highly correlated with _embedded_show_updatedHigh correlation
_embedded_show_updated is highly correlated with _embedded_show_weightHigh correlation
season is highly correlated with numberHigh correlation
number is highly correlated with seasonHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_weight is highly correlated with _embedded_show_updatedHigh correlation
_embedded_show_updated is highly correlated with _embedded_show_weightHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_summary and 16 other fieldsHigh correlation
summary is highly correlated with url and 3 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
url is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
name is highly correlated with _embedded_show_officialSite and 4 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 12 other fieldsHigh correlation
_links_self_href is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 13 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 10 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 17 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 11 other fieldsHigh correlation
id is highly correlated with url and 14 other fieldsHigh correlation
url is highly correlated with id and 24 other fieldsHigh correlation
name is highly correlated with id and 21 other fieldsHigh correlation
season is highly correlated with url and 13 other fieldsHigh correlation
number is highly correlated with url and 13 other fieldsHigh correlation
type is highly correlated with url and 10 other fieldsHigh correlation
airtime is highly correlated with id and 18 other fieldsHigh correlation
airstamp is highly correlated with id and 19 other fieldsHigh correlation
runtime is highly correlated with url and 21 other fieldsHigh correlation
summary is highly correlated with url and 8 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_type is highly correlated with url and 17 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 19 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_status is highly correlated with url and 9 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with url and 20 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with url and 21 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_ended is highly correlated with url and 17 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 23 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 15 other fieldsHigh correlation
_links_self_href is highly correlated with id and 24 other fieldsHigh correlation
number has 1 (1.1%) missing values Missing
runtime has 3 (3.4%) missing values Missing
_embedded_show_runtime has 13 (14.6%) missing values Missing
_embedded_show_averageRuntime has 2 (2.2%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique

Reproduction

Analysis started2022-05-10 02:22:25.031342
Analysis finished2022-05-10 02:22:54.547950
Duration29.52 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2036526.348
Minimum1969064
Maximum2324422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:54.707196image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1969064
5-th percentile1976048.4
Q11988071
median1995584
Q32032516
95-th percentile2228221.8
Maximum2324422
Range355358
Interquartile range (IQR)44445

Descriptive statistics

Standard deviation89201.47134
Coefficient of variation (CV)0.04380079414
Kurtosis2.787177186
Mean2036526.348
Median Absolute Deviation (MAD)10174
Skewness1.933946569
Sum181250845
Variance7956902489
MonotonicityNot monotonic
2022-05-09T21:22:54.817444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19779011
 
1.1%
19938251
 
1.1%
22111381
 
1.1%
22044521
 
1.1%
21975991
 
1.1%
21972921
 
1.1%
20722291
 
1.1%
20343611
 
1.1%
20325161
 
1.1%
20076861
 
1.1%
Other values (79)79
88.8%
ValueCountFrequency (%)
19690641
1.1%
19707691
1.1%
19720601
1.1%
19727141
1.1%
19760481
1.1%
19760491
1.1%
19774201
1.1%
19779011
1.1%
19792181
1.1%
19804041
1.1%
ValueCountFrequency (%)
23244221
1.1%
23244211
1.1%
23181141
1.1%
22898771
1.1%
22396111
1.1%
22111381
1.1%
22044521
1.1%
21975991
1.1%
21972921
1.1%
21761451
1.1%

url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size840.0 B
https://www.tvmaze.com/episodes/1977901/obycnaa-zensina-2x05-seria-14
 
1
https://www.tvmaze.com/episodes/1993825/the-case-solver-1x19-episode-19
 
1
https://www.tvmaze.com/episodes/2211138/tunelis-1x05-episode-5
 
1
https://www.tvmaze.com/episodes/2204452/the-motive-1x02-episode-2
 
1
https://www.tvmaze.com/episodes/2197599/peace-of-mind-with-taraji-1x05-holiday-blues-with-mary-j-blige
 
1
Other values (84)
84 

Length

Max length127
Median length98
Mean length78.97752809
Min length58

Characters and Unicode

Total characters7029
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1977901/obycnaa-zensina-2x05-seria-14
2nd rowhttps://www.tvmaze.com/episodes/2164196/ispoved-1x10-aem-tillmari
3rd rowhttps://www.tvmaze.com/episodes/1982411/volk-1x13-seria-13
4th rowhttps://www.tvmaze.com/episodes/1982412/volk-1x14-seria-14
5th rowhttps://www.tvmaze.com/episodes/2062930/god-of-ten-thousand-realms-1x05-episode-5

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977901/obycnaa-zensina-2x05-seria-141
 
1.1%
https://www.tvmaze.com/episodes/1993825/the-case-solver-1x19-episode-191
 
1.1%
https://www.tvmaze.com/episodes/2211138/tunelis-1x05-episode-51
 
1.1%
https://www.tvmaze.com/episodes/2204452/the-motive-1x02-episode-21
 
1.1%
https://www.tvmaze.com/episodes/2197599/peace-of-mind-with-taraji-1x05-holiday-blues-with-mary-j-blige1
 
1.1%
https://www.tvmaze.com/episodes/2197292/struggle-meals-1x16-potatoes-gonna-potate1
 
1.1%
https://www.tvmaze.com/episodes/2072229/top-dog-fighting-championship-6x02-majk-vooruzennyj-vs-gazi-zohan1
 
1.1%
https://www.tvmaze.com/episodes/2034361/lulu-1x02-episode-21
 
1.1%
https://www.tvmaze.com/episodes/2032516/booba-1x74-space-adventure1
 
1.1%
https://www.tvmaze.com/episodes/2007686/my-best-friends-story-1x02-episode-21
 
1.1%
Other values (79)79
88.8%

Length

2022-05-09T21:22:54.958227image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1977901/obycnaa-zensina-2x05-seria-141
 
1.1%
https://www.tvmaze.com/episodes/2164196/ispoved-1x10-aem-tillmari1
 
1.1%
https://www.tvmaze.com/episodes/1982411/volk-1x13-seria-131
 
1.1%
https://www.tvmaze.com/episodes/1982412/volk-1x14-seria-141
 
1.1%
https://www.tvmaze.com/episodes/2062930/god-of-ten-thousand-realms-1x05-episode-51
 
1.1%
https://www.tvmaze.com/episodes/2140389/going-seventeen-2020-12-28-ttt-1-hyperrealism-ver1
 
1.1%
https://www.tvmaze.com/episodes/2324421/unique-lady-2x09-episode-91
 
1.1%
https://www.tvmaze.com/episodes/2324422/unique-lady-2x10-episode-101
 
1.1%
https://www.tvmaze.com/episodes/1998598/unique-lady-2-1x09-episode-91
 
1.1%
https://www.tvmaze.com/episodes/1998599/unique-lady-2-1x10-episode-101
 
1.1%
Other values (79)79
88.8%

Most occurring characters

ValueCountFrequency (%)
e653
 
9.3%
-539
 
7.7%
s480
 
6.8%
/445
 
6.3%
t427
 
6.1%
o381
 
5.4%
w295
 
4.2%
i260
 
3.7%
p256
 
3.6%
a237
 
3.4%
Other values (30)3056
43.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4726
67.2%
Decimal Number1052
 
15.0%
Other Punctuation712
 
10.1%
Dash Punctuation539
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e653
13.8%
s480
 
10.2%
t427
 
9.0%
o381
 
8.1%
w295
 
6.2%
i260
 
5.5%
p256
 
5.4%
a237
 
5.0%
m221
 
4.7%
d190
 
4.0%
Other values (16)1326
28.1%
Decimal Number
ValueCountFrequency (%)
1236
22.4%
2147
14.0%
9140
13.3%
0122
11.6%
882
 
7.8%
475
 
7.1%
572
 
6.8%
371
 
6.7%
763
 
6.0%
644
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/445
62.5%
.178
 
25.0%
:89
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-539
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4726
67.2%
Common2303
32.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e653
13.8%
s480
 
10.2%
t427
 
9.0%
o381
 
8.1%
w295
 
6.2%
i260
 
5.5%
p256
 
5.4%
a237
 
5.0%
m221
 
4.7%
d190
 
4.0%
Other values (16)1326
28.1%
Common
ValueCountFrequency (%)
-539
23.4%
/445
19.3%
1236
10.2%
.178
 
7.7%
2147
 
6.4%
9140
 
6.1%
0122
 
5.3%
:89
 
3.9%
882
 
3.6%
475
 
3.3%
Other values (4)250
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e653
 
9.3%
-539
 
7.7%
s480
 
6.8%
/445
 
6.3%
t427
 
6.1%
o381
 
5.4%
w295
 
4.2%
i260
 
3.7%
p256
 
3.6%
a237
 
3.4%
Other values (30)3056
43.5%

name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct71
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size840.0 B
Episode 9
 
4
Episode 2
 
3
Episode 10
 
3
Episode 11
 
3
Серия 14
 
2
Other values (66)
74 

Length

Max length56
Median length46
Mean length15.76404494
Min length7

Characters and Unicode

Total characters1403
Distinct characters105
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)65.2%

Sample

1st rowСерия 14
2nd rowАэм Тиллмари
3rd rowСерия 13
4th rowСерия 14
5th rowEpisode 5

Common Values

ValueCountFrequency (%)
Episode 94
 
4.5%
Episode 23
 
3.4%
Episode 103
 
3.4%
Episode 113
 
3.4%
Серия 142
 
2.2%
Episode 72
 
2.2%
Episode 202
 
2.2%
Episode 192
 
2.2%
Episode 142
 
2.2%
Episode 132
 
2.2%
Other values (61)64
71.9%

Length

2022-05-09T21:22:55.085292image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode41
 
16.0%
6
 
2.3%
25
 
1.9%
the5
 
1.9%
серия4
 
1.6%
144
 
1.6%
94
 
1.6%
a4
 
1.6%
13
 
1.2%
283
 
1.2%
Other values (149)178
69.3%

Most occurring characters

ValueCountFrequency (%)
168
 
12.0%
e130
 
9.3%
o85
 
6.1%
i84
 
6.0%
s81
 
5.8%
d53
 
3.8%
r53
 
3.8%
p50
 
3.6%
E44
 
3.1%
n40
 
2.9%
Other values (95)615
43.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter911
64.9%
Space Separator168
 
12.0%
Uppercase Letter168
 
12.0%
Decimal Number117
 
8.3%
Other Punctuation20
 
1.4%
Dash Punctuation11
 
0.8%
Open Punctuation2
 
0.1%
Close Punctuation2
 
0.1%
Initial Punctuation2
 
0.1%
Final Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e130
14.3%
o85
 
9.3%
i84
 
9.2%
s81
 
8.9%
d53
 
5.8%
r53
 
5.8%
p50
 
5.5%
n40
 
4.4%
a39
 
4.3%
t37
 
4.1%
Other values (43)259
28.4%
Uppercase Letter
ValueCountFrequency (%)
E44
26.2%
S15
 
8.9%
L11
 
6.5%
A10
 
6.0%
P10
 
6.0%
F9
 
5.4%
T8
 
4.8%
H7
 
4.2%
C6
 
3.6%
D6
 
3.6%
Other values (20)42
25.0%
Decimal Number
ValueCountFrequency (%)
131
26.5%
224
20.5%
013
11.1%
810
 
8.5%
410
 
8.5%
39
 
7.7%
97
 
6.0%
65
 
4.3%
54
 
3.4%
74
 
3.4%
Other Punctuation
ValueCountFrequency (%)
,6
30.0%
.6
30.0%
#3
15.0%
'2
 
10.0%
:2
 
10.0%
?1
 
5.0%
Space Separator
ValueCountFrequency (%)
168
100.0%
Dash Punctuation
ValueCountFrequency (%)
-11
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Initial Punctuation
ValueCountFrequency (%)
«2
100.0%
Final Punctuation
ValueCountFrequency (%)
»2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin978
69.7%
Common324
 
23.1%
Cyrillic101
 
7.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e130
13.3%
o85
 
8.7%
i84
 
8.6%
s81
 
8.3%
d53
 
5.4%
r53
 
5.4%
p50
 
5.1%
E44
 
4.5%
n40
 
4.1%
a39
 
4.0%
Other values (40)319
32.6%
Cyrillic
ValueCountFrequency (%)
и11
 
10.9%
о9
 
8.9%
н8
 
7.9%
р8
 
7.9%
е7
 
6.9%
а5
 
5.0%
к4
 
4.0%
я4
 
4.0%
т3
 
3.0%
й3
 
3.0%
Other values (23)39
38.6%
Common
ValueCountFrequency (%)
168
51.9%
131
 
9.6%
224
 
7.4%
013
 
4.0%
-11
 
3.4%
810
 
3.1%
410
 
3.1%
39
 
2.8%
97
 
2.2%
,6
 
1.9%
Other values (12)35
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII1295
92.3%
Cyrillic101
 
7.2%
None7
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
 
13.0%
e130
 
10.0%
o85
 
6.6%
i84
 
6.5%
s81
 
6.3%
d53
 
4.1%
r53
 
4.1%
p50
 
3.9%
E44
 
3.4%
n40
 
3.1%
Other values (58)507
39.2%
Cyrillic
ValueCountFrequency (%)
и11
 
10.9%
о9
 
8.9%
н8
 
7.9%
р8
 
7.9%
е7
 
6.9%
а5
 
5.0%
к4
 
4.0%
я4
 
4.0%
т3
 
3.0%
й3
 
3.0%
Other values (23)39
38.6%
None
ValueCountFrequency (%)
ø2
28.6%
«2
28.6%
»2
28.6%
ü1
14.3%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean161.5505618
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:55.193378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3

Descriptive statistics

Standard deviation546.094689
Coefficient of variation (CV)3.380332961
Kurtosis8.324607599
Mean161.5505618
Median Absolute Deviation (MAD)0
Skewness3.183806369
Sum14378
Variance298219.4093
MonotonicityNot monotonic
2022-05-09T21:22:55.286304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
158
65.2%
48
 
9.0%
20207
 
7.9%
25
 
5.6%
33
 
3.4%
52
 
2.2%
181
 
1.1%
301
 
1.1%
61
 
1.1%
71
 
1.1%
Other values (2)2
 
2.2%
ValueCountFrequency (%)
158
65.2%
25
 
5.6%
33
 
3.4%
48
 
9.0%
52
 
2.2%
61
 
1.1%
71
 
1.1%
181
 
1.1%
271
 
1.1%
301
 
1.1%
ValueCountFrequency (%)
20207
7.9%
311
 
1.1%
301
 
1.1%
271
 
1.1%
181
 
1.1%
71
 
1.1%
61
 
1.1%
52
 
2.2%
48
9.0%
33
 
3.4%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct35
Distinct (%)39.8%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean28.53409091
Minimum1
Maximum355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:55.433571image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.35
Q15
median10
Q319
95-th percentile83.1
Maximum355
Range354
Interquartile range (IQR)14

Descriptive statistics

Standard deviation64.00663559
Coefficient of variation (CV)2.243163653
Kurtosis16.84662622
Mean28.53409091
Median Absolute Deviation (MAD)6.5
Skewness4.115612937
Sum2511
Variance4096.849399
MonotonicityNot monotonic
2022-05-09T21:22:55.545035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
27
 
7.9%
96
 
6.7%
55
 
5.6%
15
 
5.6%
85
 
5.6%
105
 
5.6%
204
 
4.5%
44
 
4.5%
174
 
4.5%
34
 
4.5%
Other values (25)39
43.8%
ValueCountFrequency (%)
15
5.6%
27
7.9%
34
4.5%
44
4.5%
55
5.6%
62
 
2.2%
73
3.4%
85
5.6%
96
6.7%
105
5.6%
ValueCountFrequency (%)
3551
 
1.1%
3181
 
1.1%
3171
 
1.1%
2361
 
1.1%
881
 
1.1%
741
 
1.1%
691
 
1.1%
581
 
1.1%
523
3.4%
441
 
1.1%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size840.0 B
regular
88 
insignificant_special
 
1

Length

Max length21
Median length7
Mean length7.157303371
Min length7

Characters and Unicode

Total characters637
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular88
98.9%
insignificant_special1
 
1.1%

Length

2022-05-09T21:22:55.652231image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:55.757909image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular88
98.9%
insignificant_special1
 
1.1%

Most occurring characters

ValueCountFrequency (%)
r176
27.6%
a90
14.1%
e89
14.0%
g89
14.0%
l89
14.0%
u88
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter636
99.8%
Connector Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r176
27.7%
a90
14.2%
e89
14.0%
g89
14.0%
l89
14.0%
u88
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin636
99.8%
Common1
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
r176
27.7%
a90
14.2%
e89
14.0%
g89
14.0%
l89
14.0%
u88
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (3)3
 
0.5%
Common
ValueCountFrequency (%)
_1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII637
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r176
27.6%
a90
14.1%
e89
14.0%
g89
14.0%
l89
14.0%
u88
13.8%
i5
 
0.8%
n3
 
0.5%
s2
 
0.3%
c2
 
0.3%
Other values (4)4
 
0.6%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size840.0 B
2020-12-28
89 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters890
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-28
2nd row2020-12-28
3rd row2020-12-28
4th row2020-12-28
5th row2020-12-28

Common Values

ValueCountFrequency (%)
2020-12-2889
100.0%

Length

2022-05-09T21:22:55.851720image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:55.936579image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-2889
100.0%

Most occurring characters

ValueCountFrequency (%)
2356
40.0%
0178
20.0%
-178
20.0%
189
 
10.0%
889
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number712
80.0%
Dash Punctuation178
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2356
50.0%
0178
25.0%
189
 
12.5%
889
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2356
40.0%
0178
20.0%
-178
20.0%
189
 
10.0%
889
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2356
40.0%
0178
20.0%
-178
20.0%
189
 
10.0%
889
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
47 
20:00
21 
21:00
12 
12:00
 
3
10:00
 
2
Other values (4)
 
4

Length

Max length5
Median length3
Mean length3.943820225
Min length3

Characters and Unicode

Total characters351
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)4.5%

Sample

1st row10:00
2nd row12:00
3rd rownan
4th rownan
5th row10:00

Common Values

ValueCountFrequency (%)
nan47
52.8%
20:0021
23.6%
21:0012
 
13.5%
12:003
 
3.4%
10:002
 
2.2%
06:001
 
1.1%
17:001
 
1.1%
00:001
 
1.1%
19:001
 
1.1%

Length

2022-05-09T21:22:56.015299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:56.148017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan47
52.8%
20:0021
23.6%
21:0012
 
13.5%
12:003
 
3.4%
10:002
 
2.2%
06:001
 
1.1%
17:001
 
1.1%
00:001
 
1.1%
19:001
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0110
31.3%
n94
26.8%
a47
13.4%
:42
 
12.0%
236
 
10.3%
119
 
5.4%
61
 
0.3%
71
 
0.3%
91
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number168
47.9%
Lowercase Letter141
40.2%
Other Punctuation42
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0110
65.5%
236
 
21.4%
119
 
11.3%
61
 
0.6%
71
 
0.6%
91
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
n94
66.7%
a47
33.3%
Other Punctuation
ValueCountFrequency (%)
:42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common210
59.8%
Latin141
40.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0110
52.4%
:42
 
20.0%
236
 
17.1%
119
 
9.0%
61
 
0.5%
71
 
0.5%
91
 
0.5%
Latin
ValueCountFrequency (%)
n94
66.7%
a47
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII351
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0110
31.3%
n94
26.8%
a47
13.4%
:42
 
12.0%
236
 
10.3%
119
 
5.4%
61
 
0.3%
71
 
0.3%
91
 
0.3%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size840.0 B
2020-12-28T12:00:00+00:00
51 
2020-12-28T21:00:00+00:00
10 
2020-12-28T04:00:00+00:00
2020-12-28T11:00:00+00:00
 
4
2020-12-28T17:00:00+00:00
 
4
Other values (11)
14 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters2225
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)10.1%

Sample

1st row2020-12-27T22:00:00+00:00
2nd row2020-12-28T00:00:00+00:00
3rd row2020-12-28T00:00:00+00:00
4th row2020-12-28T00:00:00+00:00
5th row2020-12-28T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-28T12:00:00+00:0051
57.3%
2020-12-28T21:00:00+00:0010
 
11.2%
2020-12-28T04:00:00+00:006
 
6.7%
2020-12-28T11:00:00+00:004
 
4.5%
2020-12-28T17:00:00+00:004
 
4.5%
2020-12-28T00:00:00+00:003
 
3.4%
2020-12-29T02:00:00+00:002
 
2.2%
2020-12-27T22:00:00+00:001
 
1.1%
2020-12-28T02:00:00+00:001
 
1.1%
2020-12-28T03:00:00+00:001
 
1.1%
Other values (6)6
 
6.7%

Length

2022-05-09T21:22:56.261159image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-28t12:00:00+00:0051
57.3%
2020-12-28t21:00:00+00:0010
 
11.2%
2020-12-28t04:00:00+00:006
 
6.7%
2020-12-28t11:00:00+00:004
 
4.5%
2020-12-28t17:00:00+00:004
 
4.5%
2020-12-28t00:00:00+00:003
 
3.4%
2020-12-29t02:00:00+00:002
 
2.2%
2020-12-27t22:00:00+00:001
 
1.1%
2020-12-28t02:00:00+00:001
 
1.1%
2020-12-28t03:00:00+00:001
 
1.1%
Other values (6)6
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0909
40.9%
2422
19.0%
:267
 
12.0%
-178
 
8.0%
1166
 
7.5%
T89
 
4.0%
+89
 
4.0%
886
 
3.9%
46
 
0.3%
75
 
0.2%
Other values (4)8
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1602
72.0%
Other Punctuation267
 
12.0%
Dash Punctuation178
 
8.0%
Uppercase Letter89
 
4.0%
Math Symbol89
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0909
56.7%
2422
26.3%
1166
 
10.4%
886
 
5.4%
46
 
0.4%
75
 
0.3%
94
 
0.2%
52
 
0.1%
31
 
0.1%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:267
100.0%
Dash Punctuation
ValueCountFrequency (%)
-178
100.0%
Uppercase Letter
ValueCountFrequency (%)
T89
100.0%
Math Symbol
ValueCountFrequency (%)
+89
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2136
96.0%
Latin89
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0909
42.6%
2422
19.8%
:267
 
12.5%
-178
 
8.3%
1166
 
7.8%
+89
 
4.2%
886
 
4.0%
46
 
0.3%
75
 
0.2%
94
 
0.2%
Other values (3)4
 
0.2%
Latin
ValueCountFrequency (%)
T89
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0909
40.9%
2422
19.0%
:267
 
12.0%
-178
 
8.0%
1166
 
7.5%
T89
 
4.0%
+89
 
4.0%
886
 
3.9%
46
 
0.3%
75
 
0.2%
Other values (4)8
 
0.4%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)37.2%
Missing3
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean41.37209302
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:56.357196image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.5
Q121.5
median45
Q351
95-th percentile82.5
Maximum180
Range178
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation28.89170307
Coefficient of variation (CV)0.6983379606
Kurtosis6.621850257
Mean41.37209302
Median Absolute Deviation (MAD)15
Skewness1.929247271
Sum3558
Variance834.7305062
MonotonicityNot monotonic
2022-05-09T21:22:56.443279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4520
22.5%
6016
18.0%
104
 
4.5%
274
 
4.5%
404
 
4.5%
303
 
3.4%
53
 
3.4%
1202
 
2.2%
162
 
2.2%
82
 
2.2%
Other values (22)26
29.2%
(Missing)3
 
3.4%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
53
3.4%
71
 
1.1%
82
2.2%
104
4.5%
122
2.2%
151
 
1.1%
162
2.2%
172
2.2%
ValueCountFrequency (%)
1801
 
1.1%
1301
 
1.1%
1202
 
2.2%
901
 
1.1%
6016
18.0%
512
 
2.2%
501
 
1.1%
481
 
1.1%
461
 
1.1%
4520
22.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
72 
<p>Locked in the deadliest fight of their lives, does Shatter Squad have what it takes to save the fate of the World? </p>
 
1
<p>As summer comes to the sun-soaked island of Jersey, the Hartmanns celebrate with...a chalet ski party! Kate focuses her attention on building bridges with Finn.</p>
 
1
<p>The fallout from Tessa and Mia's latest argument leads to a summit to clear the air, whil Ashley's relationship with Jane takes an unexpected twist.</p>
 
1
<p>Kate's ambition of starting a charity gets off to a rocky start, while Mia's dreams of returning to modelling become a reality. Plus, Tessa celebrates her birthday.</p>
 
1
Other values (13)
13 

Length

Max length599
Median length3
Mean length40.71910112
Min length3

Characters and Unicode

Total characters3624
Distinct characters54
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)19.1%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan72
80.9%
<p>Locked in the deadliest fight of their lives, does Shatter Squad have what it takes to save the fate of the World? </p>1
 
1.1%
<p>As summer comes to the sun-soaked island of Jersey, the Hartmanns celebrate with...a chalet ski party! Kate focuses her attention on building bridges with Finn.</p>1
 
1.1%
<p>The fallout from Tessa and Mia's latest argument leads to a summit to clear the air, whil Ashley's relationship with Jane takes an unexpected twist.</p>1
 
1.1%
<p>Kate's ambition of starting a charity gets off to a rocky start, while Mia's dreams of returning to modelling become a reality. Plus, Tessa celebrates her birthday.</p>1
 
1.1%
<p>Mia questions her relationships with some of the women following the disastrous dinner party, while Kate and Margaret regret not being more outspoken.</p>1
 
1.1%
<p>With the Staycation in full flow, the Housewives bond over a game of Truth or Dare, and Margaret's pulse is left racing by a surprise guest.</p>1
 
1.1%
<p>Tessa has high hopes for the housewives' staycation, but will everyone behave themselves?</p>1
 
1.1%
<p>Margaret hosts Coco Chanel Thompson's fourth birthday party, and the long-awaited meet-up between Kate and Tessa leaves their relationship in a sticky situation.</p>1
 
1.1%
<p>Mia gets the opportunity of a lifetime when she throws an extravagant dinner party.</p>1
 
1.1%
Other values (8)8
 
9.0%

Length

2022-05-09T21:22:56.575743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan72
 
11.6%
a25
 
4.0%
the24
 
3.9%
to18
 
2.9%
of15
 
2.4%
and14
 
2.3%
her12
 
1.9%
for7
 
1.1%
in7
 
1.1%
kate6
 
1.0%
Other values (330)421
67.8%

Most occurring characters

ValueCountFrequency (%)
531
14.7%
e344
 
9.5%
n313
 
8.6%
a310
 
8.6%
t227
 
6.3%
s203
 
5.6%
o188
 
5.2%
i174
 
4.8%
r172
 
4.7%
h132
 
3.6%
Other values (44)1030
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2823
77.9%
Space Separator534
 
14.7%
Uppercase Letter94
 
2.6%
Other Punctuation91
 
2.5%
Math Symbol76
 
2.1%
Dash Punctuation6
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e344
12.2%
n313
11.1%
a310
11.0%
t227
 
8.0%
s203
 
7.2%
o188
 
6.7%
i174
 
6.2%
r172
 
6.1%
h132
 
4.7%
l99
 
3.5%
Other values (15)661
23.4%
Uppercase Letter
ValueCountFrequency (%)
T14
14.9%
J13
13.8%
M13
13.8%
K7
7.4%
W6
 
6.4%
A6
 
6.4%
C5
 
5.3%
H5
 
5.3%
R5
 
5.3%
S4
 
4.3%
Other values (6)16
17.0%
Other Punctuation
ValueCountFrequency (%)
.26
28.6%
,21
23.1%
/19
20.9%
'15
16.5%
?4
 
4.4%
;3
 
3.3%
!2
 
2.2%
1
 
1.1%
Space Separator
ValueCountFrequency (%)
531
99.4%
 3
 
0.6%
Math Symbol
ValueCountFrequency (%)
>38
50.0%
<38
50.0%
Dash Punctuation
ValueCountFrequency (%)
-6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2917
80.5%
Common707
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e344
11.8%
n313
10.7%
a310
10.6%
t227
 
7.8%
s203
 
7.0%
o188
 
6.4%
i174
 
6.0%
r172
 
5.9%
h132
 
4.5%
l99
 
3.4%
Other values (31)755
25.9%
Common
ValueCountFrequency (%)
531
75.1%
>38
 
5.4%
<38
 
5.4%
.26
 
3.7%
,21
 
3.0%
/19
 
2.7%
'15
 
2.1%
-6
 
0.8%
?4
 
0.6%
 3
 
0.4%
Other values (3)6
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII3620
99.9%
None3
 
0.1%
Punctuation1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
531
14.7%
e344
 
9.5%
n313
 
8.6%
a310
 
8.6%
t227
 
6.3%
s203
 
5.6%
o188
 
5.2%
i174
 
4.8%
r172
 
4.8%
h132
 
3.6%
Other values (42)1026
28.3%
None
ValueCountFrequency (%)
 3
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct54
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47445.58427
Minimum802
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:56.777883image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum802
5-th percentile9788.2
Q149784
median52524
Q352784
95-th percentile58557.4
Maximum61755
Range60953
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation13419.86965
Coefficient of variation (CV)0.2828476002
Kurtosis4.595186787
Mean47445.58427
Median Absolute Deviation (MAD)2660
Skewness-2.292928412
Sum4222657
Variance180092901.4
MonotonicityNot monotonic
2022-05-09T21:22:56.906941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4978410
 
11.2%
526858
 
9.0%
524795
 
5.6%
525644
 
4.5%
526554
 
4.5%
525242
 
2.2%
521042
 
2.2%
152502
 
2.2%
570292
 
2.2%
529362
 
2.2%
Other values (44)48
53.9%
ValueCountFrequency (%)
8021
1.1%
25041
1.1%
60901
1.1%
61461
1.1%
61471
1.1%
152502
2.2%
224731
1.1%
306061
1.1%
324171
1.1%
339441
1.1%
ValueCountFrequency (%)
617551
1.1%
608091
1.1%
595551
1.1%
588211
1.1%
586451
1.1%
584261
1.1%
583671
1.1%
570292
2.2%
570091
1.1%
566551
1.1%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size840.0 B
https://www.tvmaze.com/shows/49784/the-real-housewives-of-jersey
10 
https://www.tvmaze.com/shows/52685/the-controllers
https://www.tvmaze.com/shows/52479/beauty-and-the-boss
 
5
https://www.tvmaze.com/shows/52564/nikkietutorials-layers-of-me
 
4
https://www.tvmaze.com/shows/52655/the-case-solver
 
4
Other values (49)
58 

Length

Max length67
Median length61
Mean length51.98876404
Min length39

Characters and Unicode

Total characters4627
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)44.9%

Sample

1st rowhttps://www.tvmaze.com/shows/39115/obycnaa-zensina
2nd rowhttps://www.tvmaze.com/shows/48683/ispoved
3rd rowhttps://www.tvmaze.com/shows/52181/volk
4th rowhttps://www.tvmaze.com/shows/52181/volk
5th rowhttps://www.tvmaze.com/shows/54541/god-of-ten-thousand-realms

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/49784/the-real-housewives-of-jersey10
 
11.2%
https://www.tvmaze.com/shows/52685/the-controllers8
 
9.0%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
5.6%
https://www.tvmaze.com/shows/52564/nikkietutorials-layers-of-me4
 
4.5%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
4.5%
https://www.tvmaze.com/shows/52524/forever-love2
 
2.2%
https://www.tvmaze.com/shows/52104/twisted-fate-of-love2
 
2.2%
https://www.tvmaze.com/shows/15250/the-young-turks2
 
2.2%
https://www.tvmaze.com/shows/57029/bablo2
 
2.2%
https://www.tvmaze.com/shows/52936/my-best-friends-story2
 
2.2%
Other values (44)48
53.9%

Length

2022-05-09T21:22:57.023753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/49784/the-real-housewives-of-jersey10
 
11.2%
https://www.tvmaze.com/shows/52685/the-controllers8
 
9.0%
https://www.tvmaze.com/shows/52479/beauty-and-the-boss5
 
5.6%
https://www.tvmaze.com/shows/52564/nikkietutorials-layers-of-me4
 
4.5%
https://www.tvmaze.com/shows/52655/the-case-solver4
 
4.5%
https://www.tvmaze.com/shows/52936/my-best-friends-story2
 
2.2%
https://www.tvmaze.com/shows/52181/volk2
 
2.2%
https://www.tvmaze.com/shows/52781/love-script2
 
2.2%
https://www.tvmaze.com/shows/52784/unique-lady-22
 
2.2%
https://www.tvmaze.com/shows/41490/unique-lady2
 
2.2%
Other values (44)48
53.9%

Most occurring characters

ValueCountFrequency (%)
/445
 
9.6%
t378
 
8.2%
w378
 
8.2%
s377
 
8.1%
e291
 
6.3%
o284
 
6.1%
h237
 
5.1%
m199
 
4.3%
-179
 
3.9%
.178
 
3.8%
Other values (30)1681
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3291
71.1%
Other Punctuation712
 
15.4%
Decimal Number445
 
9.6%
Dash Punctuation179
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t378
11.5%
w378
11.5%
s377
11.5%
e291
 
8.8%
o284
 
8.6%
h237
 
7.2%
m199
 
6.0%
a177
 
5.4%
v121
 
3.7%
c114
 
3.5%
Other values (16)735
22.3%
Decimal Number
ValueCountFrequency (%)
598
22.0%
465
14.6%
259
13.3%
642
9.4%
841
9.2%
935
 
7.9%
732
 
7.2%
132
 
7.2%
024
 
5.4%
317
 
3.8%
Other Punctuation
ValueCountFrequency (%)
/445
62.5%
.178
 
25.0%
:89
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3291
71.1%
Common1336
28.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t378
11.5%
w378
11.5%
s377
11.5%
e291
 
8.8%
o284
 
8.6%
h237
 
7.2%
m199
 
6.0%
a177
 
5.4%
v121
 
3.7%
c114
 
3.5%
Other values (16)735
22.3%
Common
ValueCountFrequency (%)
/445
33.3%
-179
13.4%
.178
 
13.3%
598
 
7.3%
:89
 
6.7%
465
 
4.9%
259
 
4.4%
642
 
3.1%
841
 
3.1%
935
 
2.6%
Other values (4)105
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII4627
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/445
 
9.6%
t378
 
8.2%
w378
 
8.2%
s377
 
8.1%
e291
 
6.3%
o284
 
6.1%
h237
 
5.1%
m199
 
4.3%
-179
 
3.9%
.178
 
3.8%
Other values (30)1681
36.3%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Memory size840.0 B
The Real Housewives of Jersey
10 
The Controllers
Beauty and the Boss
 
5
NikkieTutorials: Layers of Me
 
4
The Case Solver
 
4
Other values (49)
58 

Length

Max length33
Median length28
Mean length17.23595506
Min length4

Characters and Unicode

Total characters1534
Distinct characters84
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)44.9%

Sample

1st rowОбычная женщина
2nd rowИсповедь
3rd rowВолк
4th rowВолк
5th rowGod of Ten Thousand Realms

Common Values

ValueCountFrequency (%)
The Real Housewives of Jersey10
 
11.2%
The Controllers8
 
9.0%
Beauty and the Boss5
 
5.6%
NikkieTutorials: Layers of Me4
 
4.5%
The Case Solver4
 
4.5%
Forever Love2
 
2.2%
Twisted Fate of Love2
 
2.2%
The Young Turks2
 
2.2%
Bablo2
 
2.2%
My Best Friend's Story2
 
2.2%
Other values (44)48
53.9%

Length

2022-05-09T21:22:57.117734image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the34
 
12.7%
of22
 
8.2%
housewives10
 
3.7%
jersey10
 
3.7%
real10
 
3.7%
controllers8
 
3.0%
love7
 
2.6%
and6
 
2.2%
beauty5
 
1.9%
boss5
 
1.9%
Other values (109)151
56.3%

Most occurring characters

ValueCountFrequency (%)
e195
 
12.7%
179
 
11.7%
o101
 
6.6%
s90
 
5.9%
a72
 
4.7%
r68
 
4.4%
i67
 
4.4%
t61
 
4.0%
n56
 
3.7%
l53
 
3.5%
Other values (74)592
38.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1097
71.5%
Uppercase Letter238
 
15.5%
Space Separator179
 
11.7%
Other Punctuation14
 
0.9%
Decimal Number6
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e195
17.8%
o101
 
9.2%
s90
 
8.2%
a72
 
6.6%
r68
 
6.2%
i67
 
6.1%
t61
 
5.6%
n56
 
5.1%
l53
 
4.8%
h48
 
4.4%
Other values (37)286
26.1%
Uppercase Letter
ValueCountFrequency (%)
T48
20.2%
B21
 
8.8%
L18
 
7.6%
S17
 
7.1%
R17
 
7.1%
C14
 
5.9%
M13
 
5.5%
J12
 
5.0%
H11
 
4.6%
A10
 
4.2%
Other values (17)57
23.9%
Other Punctuation
ValueCountFrequency (%)
'5
35.7%
:4
28.6%
.3
21.4%
,1
 
7.1%
!1
 
7.1%
Decimal Number
ValueCountFrequency (%)
22
33.3%
02
33.3%
11
16.7%
31
16.7%
Space Separator
ValueCountFrequency (%)
179
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1278
83.3%
Common199
 
13.0%
Cyrillic57
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e195
15.3%
o101
 
7.9%
s90
 
7.0%
a72
 
5.6%
r68
 
5.3%
i67
 
5.2%
t61
 
4.8%
n56
 
4.4%
l53
 
4.1%
T48
 
3.8%
Other values (37)467
36.5%
Cyrillic
ValueCountFrequency (%)
н7
 
12.3%
а5
 
8.8%
е4
 
7.0%
к4
 
7.0%
о4
 
7.0%
В3
 
5.3%
л2
 
3.5%
п2
 
3.5%
с2
 
3.5%
и2
 
3.5%
Other values (17)22
38.6%
Common
ValueCountFrequency (%)
179
89.9%
'5
 
2.5%
:4
 
2.0%
.3
 
1.5%
22
 
1.0%
02
 
1.0%
11
 
0.5%
31
 
0.5%
,1
 
0.5%
!1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1476
96.2%
Cyrillic57
 
3.7%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e195
 
13.2%
179
 
12.1%
o101
 
6.8%
s90
 
6.1%
a72
 
4.9%
r68
 
4.6%
i67
 
4.5%
t61
 
4.1%
n56
 
3.8%
l53
 
3.6%
Other values (46)534
36.2%
Cyrillic
ValueCountFrequency (%)
н7
 
12.3%
а5
 
8.8%
е4
 
7.0%
к4
 
7.0%
о4
 
7.0%
В3
 
5.3%
л2
 
3.5%
п2
 
3.5%
с2
 
3.5%
и2
 
3.5%
Other values (17)22
38.6%
None
ValueCountFrequency (%)
Ç1
100.0%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size840.0 B
Scripted
50 
Reality
15 
Documentary
Animation
Talk Show
 
3
Other values (3)

Length

Max length11
Median length8
Mean length8.078651685
Min length4

Characters and Unicode

Total characters719
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowScripted
2nd rowDocumentary
3rd rowScripted
4th rowScripted
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted50
56.2%
Reality15
 
16.9%
Documentary9
 
10.1%
Animation6
 
6.7%
Talk Show3
 
3.4%
Variety2
 
2.2%
News2
 
2.2%
Sports2
 
2.2%

Length

2022-05-09T21:22:57.246003image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:57.359511image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted50
54.3%
reality15
 
16.3%
documentary9
 
9.8%
animation6
 
6.5%
talk3
 
3.3%
show3
 
3.3%
variety2
 
2.2%
news2
 
2.2%
sports2
 
2.2%

Most occurring characters

ValueCountFrequency (%)
t84
11.7%
i79
11.0%
e78
10.8%
r63
8.8%
c59
8.2%
S55
 
7.6%
p52
 
7.2%
d50
 
7.0%
a35
 
4.9%
y26
 
3.6%
Other values (16)138
19.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter624
86.8%
Uppercase Letter92
 
12.8%
Space Separator3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t84
13.5%
i79
12.7%
e78
12.5%
r63
10.1%
c59
9.5%
p52
8.3%
d50
8.0%
a35
5.6%
y26
 
4.2%
n21
 
3.4%
Other values (8)77
12.3%
Uppercase Letter
ValueCountFrequency (%)
S55
59.8%
R15
 
16.3%
D9
 
9.8%
A6
 
6.5%
T3
 
3.3%
V2
 
2.2%
N2
 
2.2%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin716
99.6%
Common3
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t84
11.7%
i79
11.0%
e78
10.9%
r63
8.8%
c59
8.2%
S55
7.7%
p52
 
7.3%
d50
 
7.0%
a35
 
4.9%
y26
 
3.6%
Other values (15)135
18.9%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t84
11.7%
i79
11.0%
e78
10.8%
r63
8.8%
c59
8.2%
S55
 
7.6%
p52
 
7.2%
d50
 
7.0%
a35
 
4.9%
y26
 
3.6%
Other values (16)138
19.2%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct15
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size840.0 B
Chinese
32 
English
29 
Russian
Norwegian
Korean
 
3
Other values (10)
12 

Length

Max length10
Median length7
Mean length6.93258427
Min length3

Characters and Unicode

Total characters617
Distinct characters29
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)9.0%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese32
36.0%
English29
32.6%
Russian8
 
9.0%
Norwegian5
 
5.6%
Korean3
 
3.4%
nan2
 
2.2%
Arabic2
 
2.2%
Swedish1
 
1.1%
Thai1
 
1.1%
Tagalog1
 
1.1%
Other values (5)5
 
5.6%

Length

2022-05-09T21:22:57.485634image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese32
36.0%
english29
32.6%
russian8
 
9.0%
norwegian5
 
5.6%
korean3
 
3.4%
nan2
 
2.2%
arabic2
 
2.2%
swedish1
 
1.1%
thai1
 
1.1%
tagalog1
 
1.1%
Other values (5)5
 
5.6%

Most occurring characters

ValueCountFrequency (%)
n84
13.6%
i82
13.3%
s79
12.8%
e75
12.2%
h66
10.7%
g36
5.8%
C32
 
5.2%
l30
 
4.9%
E29
 
4.7%
a27
 
4.4%
Other values (19)77
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter530
85.9%
Uppercase Letter87
 
14.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n84
15.8%
i82
15.5%
s79
14.9%
e75
14.2%
h66
12.5%
g36
6.8%
l30
 
5.7%
a27
 
5.1%
r12
 
2.3%
u11
 
2.1%
Other values (8)28
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C32
36.8%
E29
33.3%
R8
 
9.2%
N5
 
5.7%
K3
 
3.4%
T3
 
3.4%
A2
 
2.3%
L2
 
2.3%
S1
 
1.1%
H1
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin617
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n84
13.6%
i82
13.3%
s79
12.8%
e75
12.2%
h66
10.7%
g36
5.8%
C32
 
5.2%
l30
 
4.9%
E29
 
4.7%
a27
 
4.4%
Other values (19)77
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n84
13.6%
i82
13.3%
s79
12.8%
e75
12.2%
h66
10.7%
g36
5.8%
C32
 
5.2%
l30
 
4.9%
E29
 
4.7%
a27
 
4.4%
Other values (19)77
12.5%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct27
Distinct (%)30.3%
Missing0
Missing (%)0.0%
Memory size840.0 B
[]
27 
['Drama', 'Romance']
12 
['Drama', 'Crime', 'Thriller']
['Drama', 'Comedy', 'Romance']
['Crime']
Other values (22)
32 

Length

Max length33
Median length31
Mean length16.19101124
Min length2

Characters and Unicode

Total characters1441
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)18.0%

Sample

1st row['Drama', 'Crime', 'Mystery']
2nd row[]
3rd row['Drama', 'Adventure', 'Mystery']
4th row['Drama', 'Adventure', 'Mystery']
5th row['Adventure', 'Anime', 'Fantasy']

Common Values

ValueCountFrequency (%)
[]27
30.3%
['Drama', 'Romance']12
13.5%
['Drama', 'Crime', 'Thriller']9
 
10.1%
['Drama', 'Comedy', 'Romance']5
 
5.6%
['Crime']4
 
4.5%
['Comedy', 'Children']4
 
4.5%
['Drama', 'Romance', 'History']3
 
3.4%
['Comedy']3
 
3.4%
['Sports']2
 
2.2%
['Drama', 'Adventure', 'Mystery']2
 
2.2%
Other values (17)18
20.2%

Length

2022-05-09T21:22:57.589202image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama37
22.6%
27
16.5%
romance24
14.6%
comedy18
11.0%
crime17
10.4%
thriller9
 
5.5%
children5
 
3.0%
fantasy4
 
2.4%
mystery4
 
2.4%
adventure4
 
2.4%
Other values (9)15
9.1%

Most occurring characters

ValueCountFrequency (%)
'274
19.0%
a109
 
7.6%
m99
 
6.9%
r91
 
6.3%
[89
 
6.2%
]89
 
6.2%
e89
 
6.2%
,75
 
5.2%
75
 
5.2%
o52
 
3.6%
Other values (21)399
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter702
48.7%
Other Punctuation349
24.2%
Uppercase Letter137
 
9.5%
Open Punctuation89
 
6.2%
Close Punctuation89
 
6.2%
Space Separator75
 
5.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a109
15.5%
m99
14.1%
r91
13.0%
e89
12.7%
o52
7.4%
n42
 
6.0%
i42
 
6.0%
y34
 
4.8%
c29
 
4.1%
d29
 
4.1%
Other values (7)86
12.3%
Uppercase Letter
ValueCountFrequency (%)
C40
29.2%
D37
27.0%
R24
17.5%
T10
 
7.3%
A9
 
6.6%
M6
 
4.4%
F6
 
4.4%
H3
 
2.2%
S2
 
1.5%
Other Punctuation
ValueCountFrequency (%)
'274
78.5%
,75
 
21.5%
Open Punctuation
ValueCountFrequency (%)
[89
100.0%
Close Punctuation
ValueCountFrequency (%)
]89
100.0%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin839
58.2%
Common602
41.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a109
13.0%
m99
11.8%
r91
10.8%
e89
10.6%
o52
 
6.2%
n42
 
5.0%
i42
 
5.0%
C40
 
4.8%
D37
 
4.4%
y34
 
4.1%
Other values (16)204
24.3%
Common
ValueCountFrequency (%)
'274
45.5%
[89
 
14.8%
]89
 
14.8%
,75
 
12.5%
75
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII1441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'274
19.0%
a109
 
7.6%
m99
 
6.9%
r91
 
6.3%
[89
 
6.2%
]89
 
6.2%
e89
 
6.2%
,75
 
5.2%
75
 
5.2%
o52
 
3.6%
Other values (21)399
27.7%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size840.0 B
Running
55 
Ended
30 
To Be Determined
 
4

Length

Max length16
Median length7
Mean length6.730337079
Min length5

Characters and Unicode

Total characters599
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEnded
2nd rowEnded
3rd rowEnded
4th rowEnded
5th rowRunning

Common Values

ValueCountFrequency (%)
Running55
61.8%
Ended30
33.7%
To Be Determined4
 
4.5%

Length

2022-05-09T21:22:57.695914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:57.795992image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running55
56.7%
ended30
30.9%
to4
 
4.1%
be4
 
4.1%
determined4
 
4.1%

Most occurring characters

ValueCountFrequency (%)
n199
33.2%
d64
 
10.7%
i59
 
9.8%
R55
 
9.2%
u55
 
9.2%
g55
 
9.2%
e46
 
7.7%
E30
 
5.0%
8
 
1.3%
T4
 
0.7%
Other values (6)24
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter494
82.5%
Uppercase Letter97
 
16.2%
Space Separator8
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n199
40.3%
d64
 
13.0%
i59
 
11.9%
u55
 
11.1%
g55
 
11.1%
e46
 
9.3%
o4
 
0.8%
t4
 
0.8%
r4
 
0.8%
m4
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
R55
56.7%
E30
30.9%
T4
 
4.1%
B4
 
4.1%
D4
 
4.1%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin591
98.7%
Common8
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n199
33.7%
d64
 
10.8%
i59
 
10.0%
R55
 
9.3%
u55
 
9.3%
g55
 
9.3%
e46
 
7.8%
E30
 
5.1%
T4
 
0.7%
o4
 
0.7%
Other values (5)20
 
3.4%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n199
33.2%
d64
 
10.7%
i59
 
9.8%
R55
 
9.2%
u55
 
9.2%
g55
 
9.2%
e46
 
7.7%
E30
 
5.0%
8
 
1.3%
T4
 
0.7%
Other values (6)24
 
4.0%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct23
Distinct (%)30.3%
Missing13
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean44.10526316
Minimum2
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:57.873567image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q126.5
median45
Q360
95-th percentile97.5
Maximum180
Range178
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation29.57727909
Coefficient of variation (CV)0.6706065666
Kurtosis6.156676718
Mean44.10526316
Median Absolute Deviation (MAD)15
Skewness1.841450803
Sum3352
Variance874.8154386
MonotonicityNot monotonic
2022-05-09T21:22:57.988787image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
4519
21.3%
6017
19.1%
205
 
5.6%
104
 
4.5%
274
 
4.5%
304
 
4.5%
53
 
3.4%
382
 
2.2%
1202
 
2.2%
512
 
2.2%
Other values (13)14
15.7%
(Missing)13
14.6%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
53
3.4%
71
 
1.1%
104
4.5%
121
 
1.1%
151
 
1.1%
205
5.6%
231
 
1.1%
251
 
1.1%
ValueCountFrequency (%)
1801
 
1.1%
1301
 
1.1%
1202
 
2.2%
901
 
1.1%
6017
19.1%
512
 
2.2%
502
 
2.2%
481
 
1.1%
4519
21.3%
401
 
1.1%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct30
Distinct (%)34.5%
Missing2
Missing (%)2.2%
Infinite0
Infinite (%)0.0%
Mean40.8045977
Minimum2
Maximum181
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:58.105507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.6
Q121
median45
Q350
95-th percentile81
Maximum181
Range179
Interquartile range (IQR)29

Descriptive statistics

Standard deviation28.98509604
Coefficient of variation (CV)0.7103389734
Kurtosis6.742046909
Mean40.8045977
Median Absolute Deviation (MAD)15
Skewness1.96253247
Sum3550
Variance840.1357926
MonotonicityNot monotonic
2022-05-09T21:22:58.184119image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
4519
21.3%
6016
18.0%
305
 
5.6%
184
 
4.5%
104
 
4.5%
274
 
4.5%
503
 
3.4%
53
 
3.4%
232
 
2.2%
202
 
2.2%
Other values (20)25
28.1%
ValueCountFrequency (%)
21
 
1.1%
41
 
1.1%
53
3.4%
71
 
1.1%
82
2.2%
91
 
1.1%
104
4.5%
122
2.2%
151
 
1.1%
184
4.5%
ValueCountFrequency (%)
1811
 
1.1%
1301
 
1.1%
1202
 
2.2%
901
 
1.1%
6016
18.0%
503
 
3.4%
481
 
1.1%
471
 
1.1%
4519
21.3%
422
 
2.2%

_embedded_show_premiered
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct42
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Memory size840.0 B
2020-12-28
17 
2020-12-26
2020-12-14
2020-12-21
2020-12-07
 
4
Other values (37)
45 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters890
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)32.6%

Sample

1st row2018-10-29
2nd row2020-05-11
3rd row2020-12-07
4th row2020-12-07
5th row2020-12-21

Common Values

ValueCountFrequency (%)
2020-12-2817
19.1%
2020-12-268
 
9.0%
2020-12-148
 
9.0%
2020-12-217
 
7.9%
2020-12-074
 
4.5%
2020-11-232
 
2.2%
2020-11-302
 
2.2%
2013-12-242
 
2.2%
2020-12-272
 
2.2%
2020-04-142
 
2.2%
Other values (32)35
39.3%

Length

2022-05-09T21:22:58.298397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2817
19.1%
2020-12-148
 
9.0%
2020-12-268
 
9.0%
2020-12-217
 
7.9%
2020-12-074
 
4.5%
2020-12-202
 
2.2%
2019-01-172
 
2.2%
2020-12-242
 
2.2%
2020-04-142
 
2.2%
2020-12-272
 
2.2%
Other values (32)35
39.3%

Most occurring characters

ValueCountFrequency (%)
2257
28.9%
0197
22.1%
-178
20.0%
1151
17.0%
823
 
2.6%
418
 
2.0%
917
 
1.9%
716
 
1.8%
315
 
1.7%
613
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number712
80.0%
Dash Punctuation178
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2257
36.1%
0197
27.7%
1151
21.2%
823
 
3.2%
418
 
2.5%
917
 
2.4%
716
 
2.2%
315
 
2.1%
613
 
1.8%
55
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common890
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2257
28.9%
0197
22.1%
-178
20.0%
1151
17.0%
823
 
2.6%
418
 
2.0%
917
 
1.9%
716
 
1.8%
315
 
1.7%
613
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2257
28.9%
0197
22.1%
-178
20.0%
1151
17.0%
823
 
2.6%
418
 
2.0%
917
 
1.9%
716
 
1.8%
315
 
1.7%
613
 
1.5%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
59 
2020-12-28
2021-01-18
2021-01-07
 
3
2020-12-30
 
3
Other values (7)
10 

Length

Max length10
Median length3
Mean length5.359550562
Min length3

Characters and Unicode

Total characters477
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)5.6%

Sample

1st row2021-01-07
2nd row2021-02-08
3rd row2020-12-28
4th row2020-12-28
5th rownan

Common Values

ValueCountFrequency (%)
nan59
66.3%
2020-12-288
 
9.0%
2021-01-186
 
6.7%
2021-01-073
 
3.4%
2020-12-303
 
3.4%
2021-01-253
 
3.4%
2021-01-052
 
2.2%
2021-02-081
 
1.1%
2020-12-311
 
1.1%
2021-02-201
 
1.1%
Other values (2)2
 
2.2%

Length

2022-05-09T21:22:58.404771image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan59
66.3%
2020-12-288
 
9.0%
2021-01-186
 
6.7%
2021-01-073
 
3.4%
2020-12-303
 
3.4%
2021-01-253
 
3.4%
2021-01-052
 
2.2%
2021-02-081
 
1.1%
2020-12-311
 
1.1%
2021-02-201
 
1.1%
Other values (2)2
 
2.2%

Most occurring characters

ValueCountFrequency (%)
n118
24.7%
289
18.7%
071
14.9%
-60
12.6%
a59
12.4%
151
10.7%
815
 
3.1%
55
 
1.0%
74
 
0.8%
34
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number240
50.3%
Lowercase Letter177
37.1%
Dash Punctuation60
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
289
37.1%
071
29.6%
151
21.2%
815
 
6.2%
55
 
2.1%
74
 
1.7%
34
 
1.7%
61
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
n118
66.7%
a59
33.3%
Dash Punctuation
ValueCountFrequency (%)
-60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common300
62.9%
Latin177
37.1%

Most frequent character per script

Common
ValueCountFrequency (%)
289
29.7%
071
23.7%
-60
20.0%
151
17.0%
815
 
5.0%
55
 
1.7%
74
 
1.3%
34
 
1.3%
61
 
0.3%
Latin
ValueCountFrequency (%)
n118
66.7%
a59
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n118
24.7%
289
18.7%
071
14.9%
-60
12.6%
a59
12.4%
151
10.7%
815
 
3.1%
55
 
1.0%
74
 
0.8%
34
 
0.8%

_embedded_show_officialSite
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)53.9%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
17 
https://www.itv.com/hub/the-real-housewives-of-jersey/
10 
https://programme.mytvsuper.com/tc/130336/
https://www.iqiyi.com/a_c4m3iuc94t.html
 
4
https://youtube.com/playlist?list=PLRpysEUKISbLtgIeg_-N1px7xJWsTACof
 
4
Other values (43)
49 

Length

Max length92
Median length72
Mean length39.31460674
Min length3

Characters and Unicode

Total characters3499
Distinct characters76
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)41.6%

Sample

1st rowhttps://premier.one/show/8405
2nd rowhttps://premier.one/collections/134
3rd rowhttps://premier.one/show/12339
4th rowhttps://premier.one/show/12339
5th rowhttps://v.qq.com/detail/m/mzc002007995z4v.html

Common Values

ValueCountFrequency (%)
nan17
19.1%
https://www.itv.com/hub/the-real-housewives-of-jersey/10
 
11.2%
https://programme.mytvsuper.com/tc/130336/5
 
5.6%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
4.5%
https://youtube.com/playlist?list=PLRpysEUKISbLtgIeg_-N1px7xJWsTACof4
 
4.5%
https://tv.nrk.no/serie/bablo2
 
2.2%
https://v.qq.com/x/search/?q=+%E4%BB%8A%E5%A4%95%E4%BD%95%E5%A4%95&stag=0&smartbox_ab=2
 
2.2%
https://www.tytnetwork.com2
 
2.2%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.2%
https://premier.one/show/123392
 
2.2%
Other values (38)39
43.8%

Length

2022-05-09T21:22:58.517529image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan17
19.1%
https://www.itv.com/hub/the-real-housewives-of-jersey10
 
11.2%
https://programme.mytvsuper.com/tc/1303365
 
5.6%
https://www.iqiyi.com/a_c4m3iuc94t.html4
 
4.5%
https://youtube.com/playlist?list=plrpyseukisbltgieg_-n1px7xjwstacof4
 
4.5%
https://v.qq.com/detail/m/mzc00200dnvb1wh.html2
 
2.2%
http://www.iqiyi.com/a_19rrhvpyyp.html2
 
2.2%
https://premier.one/show/123392
 
2.2%
https://www.tytnetwork.com2
 
2.2%
https://v.qq.com/x/search/?q=+%e4%bb%8a%e5%a4%95%e4%bd%95%e5%a4%95&stag=0&smartbox_ab2
 
2.2%
Other values (38)39
43.8%

Most occurring characters

ValueCountFrequency (%)
/308
 
8.8%
t297
 
8.5%
e207
 
5.9%
s199
 
5.7%
o162
 
4.6%
h150
 
4.3%
.134
 
3.8%
p129
 
3.7%
w126
 
3.6%
a117
 
3.3%
Other values (66)1670
47.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2413
69.0%
Other Punctuation560
 
16.0%
Decimal Number253
 
7.2%
Uppercase Letter156
 
4.5%
Dash Punctuation85
 
2.4%
Math Symbol17
 
0.5%
Connector Punctuation15
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t297
 
12.3%
e207
 
8.6%
s199
 
8.2%
o162
 
6.7%
h150
 
6.2%
p129
 
5.3%
w126
 
5.2%
a117
 
4.8%
r116
 
4.8%
m115
 
4.8%
Other values (16)795
32.9%
Uppercase Letter
ValueCountFrequency (%)
E14
 
9.0%
L12
 
7.7%
A12
 
7.7%
P11
 
7.1%
B9
 
5.8%
I9
 
5.8%
T9
 
5.8%
C9
 
5.8%
U9
 
5.8%
S7
 
4.5%
Other values (16)55
35.3%
Other Punctuation
ValueCountFrequency (%)
/308
55.0%
.134
23.9%
:72
 
12.9%
%25
 
4.5%
?9
 
1.6%
&6
 
1.1%
'2
 
0.4%
,2
 
0.4%
!1
 
0.2%
#1
 
0.2%
Decimal Number
ValueCountFrequency (%)
038
15.0%
337
14.6%
133
13.0%
430
11.9%
923
9.1%
523
9.1%
221
8.3%
620
7.9%
716
6.3%
812
 
4.7%
Math Symbol
ValueCountFrequency (%)
=15
88.2%
+2
 
11.8%
Dash Punctuation
ValueCountFrequency (%)
-85
100.0%
Connector Punctuation
ValueCountFrequency (%)
_15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2569
73.4%
Common930
 
26.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t297
 
11.6%
e207
 
8.1%
s199
 
7.7%
o162
 
6.3%
h150
 
5.8%
p129
 
5.0%
w126
 
4.9%
a117
 
4.6%
r116
 
4.5%
m115
 
4.5%
Other values (42)951
37.0%
Common
ValueCountFrequency (%)
/308
33.1%
.134
14.4%
-85
 
9.1%
:72
 
7.7%
038
 
4.1%
337
 
4.0%
133
 
3.5%
430
 
3.2%
%25
 
2.7%
923
 
2.5%
Other values (14)145
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3499
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/308
 
8.8%
t297
 
8.5%
e207
 
5.9%
s199
 
5.7%
o162
 
4.6%
h150
 
4.3%
.134
 
3.8%
p129
 
3.7%
w126
 
3.6%
a117
 
3.3%
Other values (66)1670
47.7%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct35
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.73033708
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:58.616075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q117
median25
Q341
95-th percentile75.4
Maximum94
Range93
Interquartile range (IQR)24

Descriptive statistics

Standard deviation25.26710224
Coefficient of variation (CV)0.7719780636
Kurtosis-0.4311946157
Mean32.73033708
Median Absolute Deviation (MAD)10
Skewness0.8893012114
Sum2913
Variance638.4264556
MonotonicityNot monotonic
2022-05-09T21:22:58.854942image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
7310
 
11.2%
189
 
10.1%
177
 
7.9%
156
 
6.7%
305
 
5.6%
35
 
5.6%
344
 
4.5%
293
 
3.4%
193
 
3.4%
63
 
3.4%
Other values (25)34
38.2%
ValueCountFrequency (%)
11
 
1.1%
22
 
2.2%
35
5.6%
63
 
3.4%
82
 
2.2%
101
 
1.1%
142
 
2.2%
156
6.7%
177
7.9%
189
10.1%
ValueCountFrequency (%)
941
 
1.1%
921
 
1.1%
871
 
1.1%
831
 
1.1%
771
 
1.1%
7310
11.2%
682
 
2.2%
671
 
1.1%
652
 
2.2%
531
 
1.1%

_embedded_show_dvdCountry
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
89 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters267
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan89
100.0%

Length

2022-05-09T21:22:58.971279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:22:59.080768image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan89
100.0%

Most occurring characters

ValueCountFrequency (%)
n178
66.7%
a89
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter267
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n178
66.7%
a89
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin267
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n178
66.7%
a89
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII267
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n178
66.7%
a89
33.3%

_embedded_show_summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Memory size840.0 B
nan
11 
<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>
10 
<p>Ke Ying is a talented economics lecturer who is forced to help psychopath Feng Xiao Sheng gain real power within his corporation. The street smart Xiao Wu is a police informant, and when he discovers Fu's company is laundering money with foreign bank accounts, he uses his position as Feng Xiao Sheng's right-hand man to collect evidence. He befriends Ke Ying, and the two work together to destroy the criminal organization.</p>
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>
 
4
<p><b>NikkieTutorials: Layers of Me</b> giving fans a peek behind the curtain of Dutch born beauty mogul Nikkie de Jager's private life. The series was filmed over the last 2.5 years, following Nikkie through the biggest moments of her off-camera career and opening up about the challenges of navigating fame. From talking about the cruel bullying she endured as a child, to experiencing the painful loss of her brother to cancer and learning how to acknowledge her emotions, in this exclusive, intimate series Nikkie shares a behind-the-scenes look at her life with her ever growing audience, culminating with the artist's very public coming out as a transwoman and the events that followed. Beyond the trials and tribulations, the series gives a peek into Nikkie's love life with fiancé, Dylan, along with pivotal moments in her career, such as becoming appointed as Global Artistry Adviser for Marc Jacobs Beauty and collaborating with well-known celebrities.</p>
 
4
Other values (44)
52 

Length

Max length966
Median length640
Mean length372.4382022
Min length3

Characters and Unicode

Total characters33147
Distinct characters87
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)40.4%

Sample

1st row<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>
2nd row<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>
3rd rownan
4th rownan
5th row<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>

Common Values

ValueCountFrequency (%)
nan11
 
12.4%
<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>10
 
11.2%
<p>Ke Ying is a talented economics lecturer who is forced to help psychopath Feng Xiao Sheng gain real power within his corporation. The street smart Xiao Wu is a police informant, and when he discovers Fu's company is laundering money with foreign bank accounts, he uses his position as Feng Xiao Sheng's right-hand man to collect evidence. He befriends Ke Ying, and the two work together to destroy the criminal organization.</p>8
 
9.0%
<p>The play is set in the turbulent period of the Republic of China in Shanghai. In a turbulent era, the forensic doctor Che Suwei and the gentleman detective Gu Yuan are intertwined with various forces. "Deputy Inspector Kang Yichen, and the innocent and lively reporter Cao Qingluo worked together to crack out a number of weird and curious cases, and restore the truth.</p>4
 
4.5%
<p><b>NikkieTutorials: Layers of Me</b> giving fans a peek behind the curtain of Dutch born beauty mogul Nikkie de Jager's private life. The series was filmed over the last 2.5 years, following Nikkie through the biggest moments of her off-camera career and opening up about the challenges of navigating fame. From talking about the cruel bullying she endured as a child, to experiencing the painful loss of her brother to cancer and learning how to acknowledge her emotions, in this exclusive, intimate series Nikkie shares a behind-the-scenes look at her life with her ever growing audience, culminating with the artist's very public coming out as a transwoman and the events that followed. Beyond the trials and tribulations, the series gives a peek into Nikkie's love life with fiancé, Dylan, along with pivotal moments in her career, such as becoming appointed as Global Artistry Adviser for Marc Jacobs Beauty and collaborating with well-known celebrities.</p>4
 
4.5%
<p>A daring, funny, and brutally honest show that covers politics, entertainment, movies, sports, and pop culture.</p>2
 
2.2%
<p>Welcome to <b>Bablo</b>, the world's best library!</p>2
 
2.2%
<p>Ju Xuanwen (Wan Yan Lo-yun) is a man with a noble appearance and many virtues. It is a pity that he fell ill with neurosis at a young age - after an unexplained car accident he falls into a delusional state and considers himself a prince. Since then, he no longer cares about the activities of his company and concentrates on becoming emperor.<br />Lo Huai (Chuang Da Fei) - psychiatrist on the verge of bankruptcy. Because of the need for money, she took responsibility for the treatment of Ju Xuanwen. However, she did not expect her peaceful days to end one day. Spending time together, they began to fall in love with each other.</p>2
 
2.2%
<p>A story that follows two people's brave pursuit of love from their campus days to their humble beginnings as they enter the workplace to chase after their dreams together.</p>2
 
2.2%
<p>During the Yin Dynasty, Dong Yue, a brave general in the Dingyuan Rebellion, was sent back in time to stop a war that would claim the lives of countless innocents. She sets out to murder corrupted officer Lu Yuantong in an attempt to prevent war, and during her journey she met Feng Xi and Pang Yu. Pang Yu and Feng Xi were old friends who cared deeply for each other, but fell out and turn into enemies. While trying to reconcile the two brothers, Dong Yue also tries to stop Lu Yuantang's evil schemes which are poised to tear the nation apart with their help.</p>2
 
2.2%
Other values (39)42
47.2%

Length

2022-05-09T21:22:59.175368image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the326
 
5.9%
and193
 
3.5%
of175
 
3.2%
to172
 
3.1%
a151
 
2.7%
is81
 
1.5%
with79
 
1.4%
in79
 
1.4%
her65
 
1.2%
he41
 
0.7%
Other values (1394)4136
75.2%

Most occurring characters

ValueCountFrequency (%)
5392
16.3%
e3163
 
9.5%
t2108
 
6.4%
a1994
 
6.0%
n1947
 
5.9%
o1931
 
5.8%
i1900
 
5.7%
s1681
 
5.1%
r1601
 
4.8%
h1306
 
3.9%
Other values (77)10124
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25273
76.2%
Space Separator5409
 
16.3%
Uppercase Letter980
 
3.0%
Other Punctuation826
 
2.5%
Math Symbol492
 
1.5%
Dash Punctuation87
 
0.3%
Decimal Number63
 
0.2%
Open Punctuation8
 
< 0.1%
Close Punctuation8
 
< 0.1%
Currency Symbol1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3163
12.5%
t2108
 
8.3%
a1994
 
7.9%
n1947
 
7.7%
o1931
 
7.6%
i1900
 
7.5%
s1681
 
6.7%
r1601
 
6.3%
h1306
 
5.2%
l1033
 
4.1%
Other values (21)6609
26.2%
Uppercase Letter
ValueCountFrequency (%)
S105
 
10.7%
T91
 
9.3%
W67
 
6.8%
Y65
 
6.6%
F61
 
6.2%
H59
 
6.0%
J51
 
5.2%
L44
 
4.5%
X44
 
4.5%
A42
 
4.3%
Other values (16)351
35.8%
Other Punctuation
ValueCountFrequency (%)
,305
36.9%
.258
31.2%
/124
15.0%
'85
 
10.3%
"24
 
2.9%
!11
 
1.3%
:10
 
1.2%
?7
 
0.8%
&1
 
0.1%
;1
 
0.1%
Decimal Number
ValueCountFrequency (%)
017
27.0%
213
20.6%
110
15.9%
37
11.1%
56
 
9.5%
95
 
7.9%
72
 
3.2%
81
 
1.6%
41
 
1.6%
61
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
-68
78.2%
11
 
12.6%
8
 
9.2%
Space Separator
ValueCountFrequency (%)
5392
99.7%
 17
 
0.3%
Math Symbol
ValueCountFrequency (%)
>246
50.0%
<246
50.0%
Open Punctuation
ValueCountFrequency (%)
(8
100.0%
Close Punctuation
ValueCountFrequency (%)
)8
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin26253
79.2%
Common6894
 
20.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3163
12.0%
t2108
 
8.0%
a1994
 
7.6%
n1947
 
7.4%
o1931
 
7.4%
i1900
 
7.2%
s1681
 
6.4%
r1601
 
6.1%
h1306
 
5.0%
l1033
 
3.9%
Other values (47)7589
28.9%
Common
ValueCountFrequency (%)
5392
78.2%
,305
 
4.4%
.258
 
3.7%
>246
 
3.6%
<246
 
3.6%
/124
 
1.8%
'85
 
1.2%
-68
 
1.0%
"24
 
0.3%
 17
 
0.2%
Other values (20)129
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII33103
99.9%
None25
 
0.1%
Punctuation19
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5392
16.3%
e3163
 
9.6%
t2108
 
6.4%
a1994
 
6.0%
n1947
 
5.9%
o1931
 
5.8%
i1900
 
5.7%
s1681
 
5.1%
r1601
 
4.8%
h1306
 
3.9%
Other values (69)10080
30.5%
None
ValueCountFrequency (%)
 17
68.0%
é4
 
16.0%
ā1
 
4.0%
å1
 
4.0%
ç1
 
4.0%
ı1
 
4.0%
Punctuation
ValueCountFrequency (%)
11
57.9%
8
42.1%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct54
Distinct (%)60.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1633105721
Minimum1609118201
Maximum1652117487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size840.0 B
2022-05-09T21:22:59.297123image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1609118201
5-th percentile1609535141
Q11612478145
median1639852705
Q31649262439
95-th percentile1651686450
Maximum1652117487
Range42999286
Interquartile range (IQR)36784294

Descriptive statistics

Standard deviation16679199.84
Coefficient of variation (CV)0.01021317826
Kurtosis-1.610969039
Mean1633105721
Median Absolute Deviation (MAD)11657537
Skewness-0.3168579903
Sum1.453464092 × 1011
Variance2.781957072 × 1014
MonotonicityNot monotonic
2022-05-09T21:22:59.407097image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165151024210
 
11.2%
16243853328
 
9.0%
16115389485
 
5.6%
16110855674
 
4.5%
16091182014
 
4.5%
16124781452
 
2.2%
16095351412
 
2.2%
16481900582
 
2.2%
16342924672
 
2.2%
16105066872
 
2.2%
Other values (44)48
53.9%
ValueCountFrequency (%)
16091182014
4.5%
16095351412
 
2.2%
16096516762
 
2.2%
16101108411
 
1.1%
16105066872
 
2.2%
16110855674
4.5%
16115389485
5.6%
16117257131
 
1.1%
16124781452
 
2.2%
16129809601
 
1.1%
ValueCountFrequency (%)
16521174871
 
1.1%
16518632662
 
2.2%
16518386471
 
1.1%
16517638721
 
1.1%
16515703161
 
1.1%
165151024210
11.2%
16509088001
 
1.1%
16505017591
 
1.1%
16499562021
 
1.1%
16497238861
 
1.1%

_links_self_href
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size840.0 B
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/1988424
 
1
https://api.tvmaze.com/episodes/1998681
 
1
https://api.tvmaze.com/episodes/1998680
 
1
https://api.tvmaze.com/episodes/1998679
 
1
Other values (84)
84 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters3471
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.1%
https://api.tvmaze.com/episodes/19884241
 
1.1%
https://api.tvmaze.com/episodes/19986811
 
1.1%
https://api.tvmaze.com/episodes/19986801
 
1.1%
https://api.tvmaze.com/episodes/19986791
 
1.1%
https://api.tvmaze.com/episodes/19986781
 
1.1%
https://api.tvmaze.com/episodes/19986761
 
1.1%
https://api.tvmaze.com/episodes/19986751
 
1.1%
https://api.tvmaze.com/episodes/19986741
 
1.1%
https://api.tvmaze.com/episodes/19986731
 
1.1%
Other values (79)79
88.8%

Length

2022-05-09T21:22:59.517642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
1.1%
https://api.tvmaze.com/episodes/20158181
 
1.1%
https://api.tvmaze.com/episodes/19640001
 
1.1%
https://api.tvmaze.com/episodes/19954051
 
1.1%
https://api.tvmaze.com/episodes/20077601
 
1.1%
https://api.tvmaze.com/episodes/19857891
 
1.1%
https://api.tvmaze.com/episodes/20396221
 
1.1%
https://api.tvmaze.com/episodes/20396231
 
1.1%
https://api.tvmaze.com/episodes/23244271
 
1.1%
https://api.tvmaze.com/episodes/23244281
 
1.1%
Other values (79)79
88.8%

Most occurring characters

ValueCountFrequency (%)
/356
 
10.3%
p267
 
7.7%
s267
 
7.7%
e267
 
7.7%
t267
 
7.7%
o178
 
5.1%
a178
 
5.1%
i178
 
5.1%
.178
 
5.1%
m178
 
5.1%
Other values (16)1157
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2225
64.1%
Other Punctuation623
 
17.9%
Decimal Number623
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p267
12.0%
s267
12.0%
e267
12.0%
t267
12.0%
o178
8.0%
a178
8.0%
i178
8.0%
m178
8.0%
h89
 
4.0%
d89
 
4.0%
Other values (3)267
12.0%
Decimal Number
ValueCountFrequency (%)
9111
17.8%
294
15.1%
183
13.3%
058
9.3%
358
9.3%
854
8.7%
445
7.2%
644
 
7.1%
738
 
6.1%
538
 
6.1%
Other Punctuation
ValueCountFrequency (%)
/356
57.1%
.178
28.6%
:89
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2225
64.1%
Common1246
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/356
28.6%
.178
14.3%
9111
 
8.9%
294
 
7.5%
:89
 
7.1%
183
 
6.7%
058
 
4.7%
358
 
4.7%
854
 
4.3%
445
 
3.6%
Other values (3)120
 
9.6%
Latin
ValueCountFrequency (%)
p267
12.0%
s267
12.0%
e267
12.0%
t267
12.0%
o178
8.0%
a178
8.0%
i178
8.0%
m178
8.0%
h89
 
4.0%
d89
 
4.0%
Other values (3)267
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3471
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/356
 
10.3%
p267
 
7.7%
s267
 
7.7%
e267
 
7.7%
t267
 
7.7%
o178
 
5.1%
a178
 
5.1%
i178
 
5.1%
.178
 
5.1%
m178
 
5.1%
Other values (16)1157
33.3%

Interactions

2022-05-09T21:22:51.273466image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:31.251089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:36.516850image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:38.429686image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:40.490980image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:42.384300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:45.725579image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:47.435718image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:49.319729image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.055493image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:32.629347image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:37.259122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:39.240550image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:41.273131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:43.423894image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:46.404546image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:48.184310image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:50.067988image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.158845image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:33.084341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:37.357870image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:39.328605image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:41.374962image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:43.679346image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:46.518087image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:48.287002image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:50.166269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.263168image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:33.507483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:37.464327image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:39.557365image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:41.470034image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:43.923731image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:46.610784image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:48.391597image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:50.258385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.361797image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:33.887118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:37.572442image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:39.652637image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:41.566725image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:44.157576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:46.711708image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:48.491933image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:50.358540image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.882785image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:34.700904image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:38.025982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:40.111268image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:41.967463image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:44.771636image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:47.046788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:48.911753image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:50.909188image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:52.983556image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:35.063223image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:38.131158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:40.205944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:42.065592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:44.947917image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:47.146299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:49.014126image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:51.002250image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:53.077578image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:35.551165image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:38.234359image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:40.312573image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:42.178917image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:45.190774image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:47.246972image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:49.112270image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:51.096264image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:53.167951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:36.113229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:38.329366image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:40.402667image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:42.285544image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:45.441222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:47.338156image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:49.209779image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:22:51.188851image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:22:59.595915image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:22:59.727651image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:22:59.869265image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:23:00.011165image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:23:00.272992image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:22:53.342064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:22:54.061653image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:22:54.259929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:22:54.391929image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01977901https://www.tvmaze.com/episodes/1977901/obycnaa-zensina-2x05-seria-14Серия 142.05.0regular2020-12-2810:002020-12-27T22:00:00+00:0046.0nan39115https://www.tvmaze.com/shows/39115/obycnaa-zensinaОбычная женщинаScriptedRussian['Drama', 'Crime', 'Mystery']Ended50.048.02018-10-292021-01-07https://premier.one/show/840536.0nan<p>Marina is in her late 30s, she has a successful business and a close-knit family. Her husband is a surgeon and her daughters study at fancy establishments. To everybody her life seems perfect. Though, it is all just a facade concealing the real problems: her husband has a mistress, her elder daughter is a slacker and drug-dealer, her youngest is a sociopath. Well, Marina herself is not really a flower-lady, but a brothel-keeper who is hiding her dark business from everyone. The truth may come out when a girl of Marina's is found dead.</p>1.610111e+09https://api.tvmaze.com/episodes/1977902
12164196https://www.tvmaze.com/episodes/2164196/ispoved-1x10-aem-tillmariАэм Тиллмари1.010.0regular2020-12-2812:002020-12-28T00:00:00+00:0048.0nan48683https://www.tvmaze.com/shows/48683/ispovedИсповедьDocumentaryRussian[]Ended48.047.02020-05-112021-02-08https://premier.one/collections/1342.0nan<p>This is not an interview, this is a confession. Revelations of the artist in the form of a monologue. The guest's opinion may not coincide with the opinion of the PREMIER platform editorial board.</p>1.637062e+09https://api.tvmaze.com/episodes/2015818
21982411https://www.tvmaze.com/episodes/1982411/volk-1x13-seria-13Серия 131.013.0regular2020-12-28nan2020-12-28T00:00:00+00:0051.0nan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/1964000
31982412https://www.tvmaze.com/episodes/1982412/volk-1x14-seria-14Серия 141.014.0regular2020-12-28nan2020-12-28T00:00:00+00:0051.0nan52181https://www.tvmaze.com/shows/52181/volkВолкScriptedRussian['Drama', 'Adventure', 'Mystery']Ended51.050.02020-12-072020-12-28https://premier.one/show/1233925.0nannan1.640436e+09https://api.tvmaze.com/episodes/1995405
42062930https://www.tvmaze.com/episodes/2062930/god-of-ten-thousand-realms-1x05-episode-5Episode 51.05.0regular2020-12-2810:002020-12-28T02:00:00+00:007.0nan54541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese['Adventure', 'Anime', 'Fantasy']Running7.07.02020-12-21nanhttps://v.qq.com/detail/m/mzc002007995z4v.html65.0nan<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1.642689e+09https://api.tvmaze.com/episodes/2007760
52140389https://www.tvmaze.com/episodes/2140389/going-seventeen-2020-12-28-ttt-1-hyperrealism-verTTT #1 (Hyperrealism Ver.)2020.044.0regular2020-12-28nan2020-12-28T03:00:00+00:0030.0nan56655https://www.tvmaze.com/shows/56655/going-seventeenGoing SeventeenVarietyKorean[]Running30.030.02017-06-12nannan18.0nan<p>Initially a series of behind-the-scenes vlogs, <b>Going Seventeen</b> has taken a more structured route since mid-2019 and is now a reality-variety show with themed episodes. Every week, the members of Seventeen play games or participate in a variety of activities for everyone's delight and entertainment. Season 2021's keyword is "Watch What You Say", meaning that anything the members say can and will be turned into content...</p>1.651764e+09https://api.tvmaze.com/episodes/1985789
62324421https://www.tvmaze.com/episodes/2324421/unique-lady-2x09-episode-9Episode 92.09.0regular2020-12-2812:002020-12-28T04:00:00+00:0040.0nan41490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese['Drama', 'Comedy', 'Romance']Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html68.0nan<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1.651863e+09https://api.tvmaze.com/episodes/2039622
72324422https://www.tvmaze.com/episodes/2324422/unique-lady-2x10-episode-10Episode 102.010.0regular2020-12-2812:002020-12-28T04:00:00+00:0040.0nan41490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese['Drama', 'Comedy', 'Romance']Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html68.0nan<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1.651863e+09https://api.tvmaze.com/episodes/2039623
81998598https://www.tvmaze.com/episodes/1998598/unique-lady-2-1x09-episode-9Episode 91.09.0regular2020-12-28nan2020-12-28T04:00:00+00:0045.0nan52784https://www.tvmaze.com/shows/52784/unique-lady-2Unique Lady 2ScriptedChinese['Comedy', 'Fantasy', 'Romance']Running45.045.02020-12-24nannan17.0nan<p>Lin Luojing enters the XR system due to a technology competition, and time-travels to the Sheng Yuan Dynasty of the game. To return back to reality, she has to find her true love and max the "favorability points". In the midst of exchanging tactics with arrogant prince Zhong Wu Mei, her former personal guard Liu Xiu Wen returns to the capital, this time with a new identity as the Persian Prince. Liu Xiu Wen vows to wage war on Zhong Wuyan. Facing both internal and external crises and conflicts, how will Lin Luojing resolve it and embark on her journey back home?</p>1.609652e+09https://api.tvmaze.com/episodes/2324427
91998599https://www.tvmaze.com/episodes/1998599/unique-lady-2-1x10-episode-10Episode 101.010.0regular2020-12-28nan2020-12-28T04:00:00+00:0045.0nan52784https://www.tvmaze.com/shows/52784/unique-lady-2Unique Lady 2ScriptedChinese['Comedy', 'Fantasy', 'Romance']Running45.045.02020-12-24nannan17.0nan<p>Lin Luojing enters the XR system due to a technology competition, and time-travels to the Sheng Yuan Dynasty of the game. To return back to reality, she has to find her true love and max the "favorability points". In the midst of exchanging tactics with arrogant prince Zhong Wu Mei, her former personal guard Liu Xiu Wen returns to the capital, this time with a new identity as the Persian Prince. Liu Xiu Wen vows to wage war on Zhong Wuyan. Facing both internal and external crises and conflicts, how will Lin Luojing resolve it and embark on her journey back home?</p>1.609652e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
791994145https://www.tvmaze.com/episodes/1994145/the-real-housewives-of-jersey-1x04-i-should-cocoI Should Coco1.04.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>Margaret hosts Coco Chanel Thompson's fourth birthday party, and the long-awaited meet-up between Kate and Tessa leaves their relationship in a sticky situation.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/1955318
801994146https://www.tvmaze.com/episodes/1994146/the-real-housewives-of-jersey-1x05-highcliffe-high-classHighcliffe, High Class1.05.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>Tessa has high hopes for the housewives' staycation, but will everyone behave themselves?</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/1996399
811997350https://www.tvmaze.com/episodes/1997350/the-real-housewives-of-jersey-1x06-a-grave-concernA Grave Concern1.06.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>With the Staycation in full flow, the Housewives bond over a game of Truth or Dare, and Margaret's pulse is left racing by a surprise guest.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/2042003
821997351https://www.tvmaze.com/episodes/1997351/the-real-housewives-of-jersey-1x07-ladies-who-launchLadies Who Launch1.07.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>Mia questions her relationships with some of the women following the disastrous dinner party, while Kate and Margaret regret not being more outspoken.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/1996689
831997352https://www.tvmaze.com/episodes/1997352/the-real-housewives-of-jersey-1x08-fake-orgasm-addictsFake Orgasm Addicts1.08.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>Kate's ambition of starting a charity gets off to a rocky start, while Mia's dreams of returning to modelling become a reality. Plus, Tessa celebrates her birthday.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/1950703
841997353https://www.tvmaze.com/episodes/1997353/the-real-housewives-of-jersey-1x09-a-splash-for-ashA Splash for Ash1.09.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>The fallout from Tessa and Mia's latest argument leads to a summit to clear the air, whil Ashley's relationship with Jane takes an unexpected twist.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/2050241
851997354https://www.tvmaze.com/episodes/1997354/the-real-housewives-of-jersey-1x10-la-finnLa Finn1.010.0regular2020-12-2821:002020-12-28T21:00:00+00:0060.0<p>As summer comes to the sun-soaked island of Jersey, the Hartmanns celebrate with...a chalet ski party! Kate focuses her attention on building bridges with Finn.</p>49784https://www.tvmaze.com/shows/49784/the-real-housewives-of-jerseyThe Real Housewives of JerseyRealityEnglish[]Running60.060.02020-12-28nanhttps://www.itv.com/hub/the-real-housewives-of-jersey/73.0nan<p><b>The Real Housewives of Jersey</b> will see some of the island's most fabulous Housewives embrace all the island has to offer – from tranquil beaches, to the most glamourous parties. The series will give viewers a unique insight into the lifestyles of Jersey's biggest characters and promises to bring fun, laughter and, of course, plenty of glitz. Filming started this month. </p>1.651510e+09https://api.tvmaze.com/episodes/1970536
861972714https://www.tvmaze.com/episodes/1972714/wwe-monday-night-raw-27x52-1440-tropicana-field-in-st-petersburg-fl#1440 - Tropicana Field in St. Petersburg, FL27.052.0regular2020-12-2820:002020-12-29T01:00:00+00:00180.0nan802https://www.tvmaze.com/shows/802/wwe-monday-night-rawWWE Monday Night RAWSportsEnglish[]Running180.0181.01993-01-11nanhttp://www.wwe.com/94.0nan<p><b>WWE Monday Night RAW</b> is World Wrestling Entertainment's (formerly the WWF and the WWWF before that) premiere wrestling event and brand. Since its launch in 1993, WWE Monday Night RAW continues to air live on Monday nights. It is generally seen as the company's flagship program due to its prolific history, high ratings, weekly live format, and emphasis on pay-per-views. Monday Night RAW is high profile enough to attract frequent visits from celebrities who usually serve as guest hosts for a single live event. Since its first episode, the show has been broadcast live or recorded from more than 197 different arenas in 165 cities and towns in seven different nations: including the United States, Canada, the United Kingdom twice a year, Afghanistan for a special Tribute to the Troops, Germany, Japan, Italy and Mexico.</p>1.649724e+09https://api.tvmaze.com/episodes/2005420
871987975https://www.tvmaze.com/episodes/1987975/dr-pimple-popper-5x01-leave-it-to-the-nevusLeave It to the Nevus5.01.0regular2020-12-2821:002020-12-29T02:00:00+00:0060.0<p>With pandemic safety protocols in place, Dr. Lee reopens her office. Monica has a large birthmark growing on the side of her face. Jackie has a melon-sized lump on the back of her shoulder. Reginald has large, rare growths on the back of his head.</p>34301https://www.tvmaze.com/shows/34301/dr-pimple-popperDr. Pimple PopperRealityEnglish['Medical']Running60.060.02018-07-11nanhttps://go.tlc.com/show/dr-pimple-popper-tlc92.0nan<p>Dr. Sandra Lee is a renowned dermatological surgeon who is tasked with removing life-altering growths from her patients' skin so they can try to reclaim their lives.</p>1.650502e+09https://api.tvmaze.com/episodes/1985483
882152587https://www.tvmaze.com/episodes/2152587/gang-wars-princes-1x12-serija-12Serija 121.012.0regular2020-12-2821:002020-12-29T02:00:00+00:0045.0nan57009https://www.tvmaze.com/shows/57009/gang-wars-princesGang Wars. PrincesScriptedLithuanian['Drama', 'Crime', 'Thriller']EndedNaN45.02020-10-122020-12-28https://go3.lt/series/gauju-karai-princai,serial-204203617.0nan<p>Based on true events, the new Go3 original series is a crime story that may have taken place in the late 20th century in Lithuania. The story about one of the criminal groups "Princes" shows their methods of action, lifestyle and relationships with other criminal gangs.</p>1.636217e+09https://api.tvmaze.com/episodes/1985484